Automated recognition of cell images in high grade malignant lymphoma and reactive follicular hyperplasia.
In the past, the comparison of results of studies on malignant lymphomas has been biased by the use of different classifications of the diseases and to an even greater extent by subjective interpretation in the classification of the tumour cells. To overcome these short-comings, we have developed cytometric features specifically for automated recognition of cell images from high grade malignant non-Hodgkin's lymphomas (NHL) and reactive lymphoid lesions. This study used a colour TV-microscope system, high resolution scanning (13.3 pixel/microns), and image processing to study a total of 3600 lymphoid cells from 15 high grade malignant NHL and three tonsils. Sixteen out of 64 features, especially developed for image analysis in cytological preparations, have been evaluated. Because of a considerable overlap of all the single features, no feature on its own allows reliable discrimination. But, multivariant analysis of suitable feature combinations resulted in reliable identification and discrimination of the most frequently occurring cell types. We show that the lymphocytes, centrocytes, centroblasts, immunoblasts and lymphoblasts, as they are defined by subjective morphological criteria in the Kiel-classification of malignant NHL, also form distinctive subpopulations on the basis of their objective mathematical cell features. Furthermore, we have shown that there are distinctive differences between the lymphoma cells and their benign counterparts derived from reactive lymphoid lesions.
Bergmann
M
M
Institute of Pathology, University of Würzburg, FRG.
Heyn
H
H
Müller-Hermelink
H K
HK
Harms
H
H
Aus
H M
HM
D003937:Diagnosis, Differential; D006801:Humans; D006965:Hyperplasia / Q000473:pathology; D007091:Image Processing, Computer-Assisted; D007621:Karyotyping; D008214:Lymphocytes / Q000473:pathology*; D008228:Lymphoma, Non-Hodgkin / Q000145:classification / Q000473:pathology*; D015203:Reproducibility of Results; D014069:Tonsillitis / Q000473:pathology*